[{"data":1,"prerenderedAt":614},["ShallowReactive",2],{"uc-newsroom-drafting-and-article-summaries":3,"uc-regulations":393},{"useCase":4,"evidence":181,"blitsAiDeployments":285,"benchmarks":286,"indicative":293,"related":296,"indexability":391,"includeUnpublished":187},{"title":5,"shortTitle":6,"seoTitle":7,"metaDescription":8,"status":9,"definition":10,"aliases":11,"industries":16,"functions":18,"patterns":21,"channels":24,"audience":25,"autonomy":26,"adoptionStage":27,"problem":28,"problemStats":29,"howItWorks":30,"valueDrivers":31,"kpis":35,"indicativeValue":42,"macroEstimates":71,"feasibility":72,"implementation":85,"risk":127,"blitsAi":157,"faq":159,"related":172,"datePublished":176,"dateModified":176,"lastVerified":176,"changelog":177,"slug":180},"AI drafting and article summaries for newsrooms with editor review","Newsroom drafting and summaries","AI newsroom drafting and article summaries","Newsrooms use AI to draft routine stories and summarize articles under journalist review. Newsquest reports 10,000+ AI aided articles; the BBC announced pilots.","published","Newsroom AI turns a reporter's verified notes into a draft story and long articles into key point summaries, which a journalist edits before anything is published. Publishers use it for routine stories such as community news and event listings, and for summaries at the top of articles.",[12,13,14,15],"AI assisted reporting","AI article summaries","AI key points for news","newsroom copilot",[17],"media-and-entertainment",[19,20],"operations","knowledge-management",[22,23],"content-generation","summarization",[],"employee-facing","copilot","early-adopters","Regional and local newsrooms receive far more material than reporters can turn into stories:\npress releases, council notices, community announcements, event listings and stories supplied by\npartner services. The BBC describes the same bottleneck for stories from the Local Democracy\nReporting Service, which arrive at a rate that means not all can be rewritten into BBC style and\npublished. Newsquest says this routine content is necessary but does not call for investigative\nskills or human insight, and that doing it quickly frees traditional journalists for more complex\nstories.\n\nReaders add a second demand. The BBC says bite sized content is increasingly favoured by news\nreaders, especially younger audiences, and it is piloting short summaries at the top of\nlonger stories. Writing a summary for every article by hand is one more task for an editor.",[],"1. **Gather verified material.** The reporter collects the facts: the press release, the council\n   document, quotes and figures. At Newsquest the reporter places the reliable and checked\n   information in a notes field, which limits the draft to facts the journalist has checked, though\n   the reviewer must still catch anything the model adds.\n2. **Generate a draft or a summary.** For a draft, the AI turns the notes into an article in the\n   house style. The BBC's Style Assist writes new drafts in BBC style from supplied stories. For a\n   summary, the AI reads the finished article and returns a short list of key points from one\n   approved prompt.\n3. **Review and edit.** A journalist checks every claim against the source, fixes errors and\n   tone. Gannett's summaries carry a disclaimer that they were\n   reviewed by a journalist before publication.\n4. **Publish with disclosure.** The page states that AI was used for the summary or the draft\n   and which part of the page it covers. The BBC says it will disclose where AI has been used.\n5. **Monitor after publication.** Editors read a sample of published items, collect corrections\n   and track reader behavior on summaries.",[32,33,34],"employee-productivity","speed","cost-to-serve",[36,37,38,39,40,41],"productivity-gain","time-saved-per-task","interactions-handled","accuracy","error-reduction","employee-adoption",{"referenceOrg":43,"inputs":44,"formula":66,"currency":67,"period":68,"resultLabel":69,"caveat":70},"A regional news publisher that drafts routine stories with AI",[45,52,59],{"key":46,"label":47,"low":48,"high":49,"unit":50,"note":51},"routineStories","Routine stories drafted with AI per year",3000,10000,"stories per year","Editorial assumption. Newsquest reports over 10,000 articles published with AI aid across its titles by June 2024.",{"key":53,"label":54,"low":55,"high":56,"unit":57,"note":58},"minutesSaved","Net minutes saved per story after journalist review",8,20,"minutes per story","Editorial assumption. No publisher on this page has published a time saving per story; measure it in a pilot.",{"key":60,"label":61,"low":62,"high":63,"unit":64,"note":65},"hourlyCost","Loaded cost of a journalist hour",30,60,"USD per hour","Editorial assumption, replace with your own fully loaded cost.","routineStories * minutesSaved \u002F 60 * hourlyCost","USD","per year","Journalist time freed, valued at cost","Gross value of time freed only. It leaves out the cost of the tools, the extra editing when drafts are weak, corrections after publication, and whether the freed hours are used for reporting that earns more than the routine stories they replace.",[],{"complexity":73,"complexityNote":74,"dataPrerequisites":75,"integrations":80},"medium","The build needs a content management system that can host the tool inside the editing screen, an approved prompt or house style set per content type, a clear disclosure label, and an editorial policy that says which stories may use AI at all. Aftonbladet's account, as reported by the Online News Association, is that tools built into the CMS worked better than tools that required a second platform.",[76,77,78,79],"A house style guide and a set of approved published stories as examples","Verified input for every draft: the source document, quotes and figures","An editorial policy for where AI may be used and how it is disclosed","A log of corrections, linked to the tool that produced the text",[81,82,83,84],"Content management system (draft creation, summary field, publish workflow)","Wire or partner story feeds, for example local democracy reporting","Analytics for reader behavior on summaries","Corrections log and editorial audit trail",{"steps":86,"guardrails":102,"humanInTheLoop":108,"kpisToInstrument":109,"failureModes":114},[87,90,93,96,99],{"title":88,"detail":89},"Pick content types where the facts are in the input","Start with stories whose facts are all in a supplied document: event listings, community updates, press release rewrites. Leave anything that needs judgment about what is true to reporters.",{"title":91,"detail":92},"Put the tool inside the CMS","Add a button in the editing screen that fills a draft or a summary field. Aftonbladet's experience was that tools which needed a switch to another platform were far less successful.",{"title":94,"detail":95},"Fix the prompt and the review rule","Use one approved prompt per content type, as the BBC does for its summaries, and write down what the reviewing journalist must check: names, numbers, quotes, dates and attribution.",{"title":97,"detail":98},"Pilot with a named group and measure","Run the tool with a small group for a few weeks. Count drafts accepted, edits per draft, corrections after publication and minutes per story against a comparable group.",{"title":100,"detail":101},"Disclose and widen","Publish a plain statement of where AI is used, add the label on each page, then widen to more desks only when corrections stay at or below the baseline.",[103,104,105,106,107],"AI input limited to material the journalist has verified and entered","A journalist reviews and approves every draft and every summary before publication","A visible label on pages with AI assisted text or summaries","No AI drafting of stories that need investigation, sensitive reporting or legal review","Corrections traced back to the tool and reviewed monthly","The journalist owns the text: they check each claim, edit or discard the output and are accountable for what is published. Editors decide which content types may use the tool and review the corrections log. Readers can report errors in a summary through the usual corrections route.",[110,111,112,113],"Share of AI drafts and summaries published after edits, and edits per item","Corrections per thousand AI assisted items against the baseline","Minutes from input to published story for AI assisted stories","Reader behavior on summaries: share who expand them and time on the full article",[115,118,121,124],{"title":116,"detail":117},"A fluent error is published","A summary states a date or a figure the article does not contain. Review against the article, not against memory, and keep the rule that no summary goes out unreviewed.",{"title":119,"detail":120},"Review becomes a glance","Reviewers see hundreds of items and approve without checking. Sample reviews by a second editor and track the correction rate per reviewer group.",{"title":122,"detail":123},"Reporter resistance","Reporters distrust a tool they did not choose. The Online News Association reports initial resistance to summaries at Aftonbladet; include reporters in the design.",{"title":125,"detail":126},"Style drift","Drafts converge on one flat voice. Refresh the style examples and let editors tag drafts that read as generic.",{"euAiAct":128,"regulations":131,"guidance":134,"controls":147,"incidents":152},{"tier":129,"basis":130},"limited","Article 50(4) requires deployers to disclose text generated by AI that is published to inform the public on matters of public interest, unless the text has undergone human review or editorial control and a person holds editorial responsibility for it. A newsroom with a journalist who reviews and is responsible for every item meets the exception, but a label is still good practice. Newsroom drafting is not an Annex III use.",[132,133],"eu-ai-act","gdpr",[135,141],{"title":136,"issuer":137,"region":138,"url":139,"note":140},"Article 50, transparency obligations for providers and deployers of certain AI systems","European Union","europe","https:\u002F\u002Feur-lex.europa.eu\u002Feli\u002Freg\u002F2024\u002F1689\u002Foj","Sets the disclosure duty for AI generated text on matters of public interest and the exception for human review under editorial responsibility.",{"title":142,"issuer":143,"region":144,"url":145,"note":146},"Paris Charter on AI and Journalism","Reporters Without Borders and 16 partner organizations","global","https:\u002F\u002Frsf.org\u002Fen\u002Fparis-charter-ai-and-journalism","States that human decision making must remain central to daily editorial choices and that responsibilities for the use of AI systems should be assigned to humans.",[148,149,150,151],"Editorial policy that lists permitted and forbidden uses of AI","Journalist approval recorded in the CMS for every AI assisted item","Label on pages with AI assisted text or summaries","Corrections log that links each correction to the tool and the prompt version",[153],{"title":154,"url":155,"note":156},"Gannett halts AI written high school sports recaps after the Columbus Dispatch","https:\u002F\u002Fwww.mediapost.com\u002Fpublications\u002Farticle\u002F396137\u002Fgannett-tries-ai-in-bullet-point-article-summaries.html","MediaPost reports that Gannett stopped an effort to insert AI into its journalism in August 2023 after AI written sports write ups from Lede AI drew ridicule for lines such as a scoreboard being \"in hibernation until the fourth quarter\".",{"howToBuild":158},"On Blits.ai this is an **AI agent** that receives the reporter's verified notes and a content\ntype, with a **knowledge base** that holds the house style guide and approved example stories,\nretrieved with hybrid search. A **custom function** calls the publisher's CMS to create the\ndraft or fill the summary field, and an **agentic workflow** with **human in the loop approval**\nkeeps the item unpublished until a journalist approves it. Summaries use the same pattern on a\nfinished article.\n\n**Guardrails** check outputs against the style and policy rules, **PII masking** removes\npersonal data from notes before they reach a model, and **test suites** run a set of reference\nstories through the agent on every change of prompt or model. **Analytics** show volumes, and the\nplatform is **model agnostic**, so the model can differ per content type. The agent stays inside\nthe CMS editing screen through the **API channel**.",[160,163,166,169],{"question":161,"answer":162},"Do publishers publish AI summaries without review?","Gannett, the BBC and Newsquest say a journalist reviews the output. Gannett's disclaimer says the Key Points were reviewed by a journalist before publication, the BBC says its summaries are reviewed and edited before and after publication, and Newsquest says journalists review each draft to check it is accurate and well written. The Aftonbladet case study does not describe a review step for its summaries.",{"question":164,"answer":165},"How many articles can AI aided reporters produce?","Newsquest reported in June 2024 that it had published over 10,000 articles with the aid of AI, mainly press release based stories, community updates and event listings. It gave no time saving or correction rate.",{"question":167,"answer":168},"Do readers use AI summaries?","The Online News Association reports a click through rate of 43% on Aftonbladet's expandable AI summaries (53% among readers aged 19 to 36), and says elsewhere in the same case study that 40% of readers who saw the summaries expanded them. It also reports that readers who used them spent more time on the full article. These are rates reported in a case study, not a controlled test.",{"question":170,"answer":171},"Does the EU AI Act require a label on AI assisted news?","Article 50(4) requires disclosure of AI generated text published to inform the public on matters of public interest, unless a person has reviewed it and holds editorial responsibility. Many publishers add a label anyway, as the BBC says it will.",[173,174,175],"publisher-archive-answer-engine","audio-and-video-transcription-and-captioning","media-archive-metadata-tagging","2026-10-13",[178],{"date":176,"note":179},"First published","newsroom-drafting-and-article-summaries",[182,218,241,263],{"title":183,"useCases":184,"organization":185,"vendors":190,"summary":193,"stage":194,"year":195,"channels":196,"languages":197,"metrics":199,"outcomeDisclosed":207,"sources":208,"verification":213,"grade":215,"id":216,"organizationSlug":217},"Newsquest: AI assisted reporters draft routine stories that journalists review",[180],{"name":186,"anonymized":187,"country":188,"region":138,"industry":17,"wikidata":189},"Newsquest",false,"GB","Q16998932",[191],{"name":186,"role":192},"in-house","Newsquest, a UK regional publisher, equips AI assisted reporters with its own tool, News Creator. The reporter places verified information in a notes field, the AI turns it into a draft article, and a journalist reviews the draft for accuracy and quality before it is published. The content covers press release based stories, community updates and event listings. Jody Doherty-Cove, head of editorial AI, wrote in June 2024 that Newsquest had published over 10,000 articles this way. The same article describes a separate bot that finds the right freedom of information email address and drafts requests to authorities.","scaled",2024,[],[198],"en",[200],{"kpi":38,"value":49,"unit":201,"qualifier":202,"period":203,"claimant":204,"quote":205,"sourceUrl":206},"count","at-least","cumulative to June 2024, articles published with the aid of AI","organization","We’ve now published over 10,000 articles with the aid of AI, reaching millions across the UK.","https:\u002F\u002Finpublishing.co.uk\u002Farticles\u002Fhow-were-using-ai-at-newsquest-24249",true,[209],{"url":206,"title":210,"publisher":211,"date":212},"How we're using AI at Newsquest","InPublishing","2024-06-19",{"level":214,"checkedAt":176},"source-verified","B","newsquest-ai-assisted-reporters",null,{"title":219,"useCases":220,"organization":221,"vendors":224,"summary":226,"stage":227,"year":228,"channels":229,"languages":230,"metrics":231,"outcomeDisclosed":187,"sources":232,"verification":238,"grade":239,"id":240,"organizationSlug":217},"BBC News: At a glance summaries and Style Assist pilots with journalist review",[180],{"name":222,"anonymized":187,"country":188,"region":138,"industry":17,"wikidata":223},"BBC","Q9531",[225],{"name":222,"role":192},"In June 2025 the BBC announced public trials of two generative AI tools in BBC News. \"At a glance\" produces a bullet point summary of a longer story from a single approved prompt, and the summary is reviewed and edited before and after publication. \"BBC Style Assist\" takes a story submitted through the Local Democracy Reporting Service and writes a new draft in BBC house style, which a journalist reviews before it is published online. The BBC says it will disclose where AI has been used and will assess whether to release the tools more widely.","pilot",2025,[],[198],[],[233],{"url":234,"title":235,"publisher":236,"date":237},"https:\u002F\u002Ffutureweek.com\u002Fbbc-introduces-gen-ai-summary-in-news-stories\u002F","BBC Introduces Gen AI Summary in News Stories","Futureweek","2025-06-27",{"level":214,"checkedAt":176},"C","bbc-at-a-glance-and-style-assist-pilots",{"title":242,"useCases":243,"organization":244,"vendors":249,"summary":251,"stage":252,"year":195,"channels":253,"languages":254,"metrics":255,"outcomeDisclosed":187,"sources":256,"verification":261,"grade":239,"id":262,"organizationSlug":217},"USA TODAY and Gannett: AI Key Points reviewed by a journalist before publication",[180],{"name":245,"anonymized":187,"country":246,"region":247,"industry":17,"wikidata":248},"Gannett","US","north-america","Q1345971",[250],{"name":245,"role":192},"In May 2024 Gannett began adding AI generated \"Key Points\", a short list of bullets, at the top of stories on USA TODAY, according to an internal memo reported by The Verge and MediaPost. The articles carry a disclaimer that the Key Points were created with the assistance of AI and reviewed by a journalist before publication, and that no other part of the article was generated with AI. MediaPost notes that Gannett had stopped an earlier AI experiment, AI written high school sports recaps, in August 2023 after the output was ridiculed.","production",[],[198],[],[257],{"url":155,"title":258,"publisher":259,"date":260},"Gannett Tries AI In Bullet-Point Article Summaries: Report","MediaPost","2024-05-16",{"level":214,"checkedAt":176},"usa-today-gannett-key-points-summaries",{"title":264,"useCases":265,"organization":266,"vendors":270,"summary":272,"stage":252,"year":273,"channels":274,"languages":275,"metrics":277,"outcomeDisclosed":207,"sources":278,"verification":283,"grade":239,"id":284,"organizationSlug":217},"Aftonbladet: AI article summaries built into the CMS",[180],{"name":267,"anonymized":187,"country":268,"region":138,"industry":17,"wikidata":269},"Aftonbladet","SE","Q389458",[271],{"name":267,"role":192},"Aftonbladet, a Swedish newspaper, built AI generated article summaries into its content management system. They appear below the article lead as expandable text. The Online News Association reports a click through rate of 43% on the expandable summaries (53% among readers aged 19 to 36), says elsewhere in the same case study that 40% of readers who saw the summaries expanded them, and reports that readers who used them spent more time on the full article. The ONA also reports that AI generated headlines did not perform as well as hoped and that tools inside the CMS worked better than tools that needed a second platform.",2023,[],[276],"sv",[],[279],{"url":280,"title":281,"publisher":282},"https:\u002F\u002Fwww.journalists.org\u002Fnews\u002Fcase-study-swedens-aftonbladet-built-ai-driven-editorial-tools-and-an-election-chatbot","Case Study: Sweden's Aftonbladet Built AI-Driven Editorial Tools and an Election Chatbot","Online News Association",{"level":214,"checkedAt":176},"aftonbladet-ai-article-summaries",0,[287],{"kpi":38,"label":288,"unit":201,"aggregate":187,"higherIsBetter":207,"n":289,"nUpTo":285,"median":49,"min":49,"max":49,"byClaimant":290,"vendorOnly":187,"points":291},"Interactions handled",1,{"organization":289,"vendor":285,"regulator":285,"independent":285},[292],{"evidenceId":216,"organization":186,"value":49,"qualifier":202,"claimant":204,"grade":215,"pooled":207},{"low":294,"high":295},12000,200000,[297,318,347,363],{"slug":173,"title":298,"shortTitle":299,"definition":300,"status":9,"industries":301,"functions":302,"patterns":304,"audience":307,"autonomy":308,"adoptionStage":27,"evidenceCount":309,"publicEvidenceCount":309,"organizations":310,"bestGrade":215,"headline":217,"lastVerified":317,"indexable":207},"AI answer engine for readers built on a publisher's own journalism","Publisher archive answer engine","A publisher archive answer engine is a generative AI search and answer tool on a publisher's site or app that answers readers' questions from its own journalism. It answers only from that publisher's published journalism and archive, cites the articles it used, and declines to answer when its own reporting does not cover the question.",[17],[303],"customer-service",[305,306,23],"rag-knowledge-assistant","conversational-agent","customer-facing","autonomous",7,[267,311,312,313,314,315,316],"Financial Times","Forbes","Foundry","Rappler","TIME","The Washington Post","2026-09-27",{"slug":174,"title":319,"shortTitle":320,"definition":321,"status":9,"industries":322,"functions":325,"patterns":326,"audience":329,"autonomy":26,"adoptionStage":330,"evidenceCount":55,"publicEvidenceCount":309,"organizations":331,"bestGrade":215,"headline":338,"lastVerified":346,"indexable":207},"AI transcription, subtitles and captions for audio and video","Transcription and captioning","AI transcription and captioning is AI that transcribes recorded audio and video, such as podcasts, broadcasts, lessons, interviews and hearings, in several languages. It separates the speakers and produces timed transcripts, subtitles and captions for a human editor to check, delivered as files for publishing or the archive.",[17,323,324],"education","cross-industry",[19,20],[327,328,22],"speech-analytics","translation","back-office","mainstream",[332,222,333,334,335,336,337],"Ateme","Comeen","Pacers Sports & Entertainment","Sveriges Television (SVT)","University of Florida","Warner Bros. Discovery",{"kpi":339,"label":340,"unit":341,"n":289,"nUpTo":285,"kind":342,"value":343,"qualifier":344,"claimant":345,"organization":337,"vendorReported":207},"cost-reduction","Cost reduction","percent","reported",50,"exact","vendor","2026-09-26",{"slug":175,"title":348,"shortTitle":349,"definition":350,"status":9,"industries":351,"functions":352,"patterns":353,"audience":329,"autonomy":26,"adoptionStage":27,"segment":356,"evidenceCount":357,"publicEvidenceCount":357,"organizations":358,"bestGrade":215,"headline":217,"lastVerified":362,"indexable":207},"AI metadata tagging and indexing for media archives","Media archive metadata tagging","AI media archive metadata tagging watches and listens to a broadcaster's or publisher's video and audio archive and generates structured metadata describing what is in each piece of content. It captures detail such as what is shown, who appears, spoken content, on screen text, logos and objects, so content makers can find and reuse footage through natural language search instead of relying on sparse, inconsistent tags added by hand over decades.",[17],[20,19],[354,327,355],"computer-vision","classification-and-routing","content operations",3,[359,360,361],"Australian Broadcasting Corporation","Bell Media","Radiotelevisión Española (RTVE)","2026-09-28",{"slug":364,"title":365,"shortTitle":366,"definition":367,"status":9,"industries":368,"functions":370,"patterns":371,"audience":25,"autonomy":26,"adoptionStage":330,"evidenceCount":372,"publicEvidenceCount":372,"organizations":373,"bestGrade":215,"headline":385,"lastVerified":317,"indexable":207},"ambient-clinical-documentation","AI ambient scribe for clinical documentation","Ambient clinical documentation","Ambient clinical documentation is an AI scribe that listens, with the patient's consent, to the conversation between a clinician and a patient and drafts the clinical note. It often also drafts the letter or after visit summary, for the clinician to review, edit and sign in the health record; it documents and does not diagnose or decide on treatment.",[369],"healthcare",[19,20],[327,23,22],11,[374,375,376,377,378,379,380,381,382,383,384],"Beth Israel Lahey Health","BJC Health","Capio","Charité Universitätsmedizin Berlin","Great Ormond Street Hospital for Children NHS Foundation Trust","Kaiser Permanente","Mount Sinai Medical Center","PureHealth","Reid Health","Sutter Health","US Department of Veterans Affairs, Veterans Health Administration",{"kpi":386,"label":387,"unit":341,"n":388,"nUpTo":285,"kind":389,"value":390,"qualifier":344,"claimant":217,"organization":217,"vendorReported":187},"handling-time-reduction","Handling time reduction",4,"median",22.5,{"indexable":207,"reasons":392},[],[394,398,403,410,417,424,430,437,445,452,459,465,471,478,485,492,498,504,511,516,521,528,534,540,545,550,556,561,567,572,580,585,591,597,603,608],{"id":132,"label":395,"issuer":137,"region":138,"url":139,"description":396,"useCases":397,"indexable":207},"EU AI Act","Regulation (EU) 2024\u002F1689: risk based rules for AI systems, with obligations for high risk systems listed in Annex III and transparency duties under Article 50.",275,{"id":133,"label":399,"issuer":137,"region":138,"url":400,"description":401,"useCases":402,"indexable":207},"GDPR","https:\u002F\u002Feur-lex.europa.eu\u002Feli\u002Freg\u002F2016\u002F679\u002Foj","General Data Protection Regulation, including Article 22 on decisions based solely on automated processing.",246,{"id":404,"label":405,"issuer":406,"region":144,"url":407,"description":408,"useCases":409,"indexable":207},"iso-42001","ISO\u002FIEC 42001","ISO and IEC","https:\u002F\u002Fwww.iso.org\u002Fstandard\u002F81230.html","The international management system standard for AI.",143,{"id":411,"label":412,"issuer":413,"region":247,"url":414,"description":415,"useCases":416,"indexable":207},"nist-ai-rmf","NIST AI Risk Management Framework","NIST","https:\u002F\u002Fwww.nist.gov\u002Fitl\u002Fai-risk-management-framework","Voluntary US framework to map, measure, manage and govern AI risk, with a generative AI profile.",110,{"id":418,"label":419,"issuer":420,"region":138,"url":421,"description":422,"useCases":423,"indexable":207},"uk-gdpr","UK GDPR","Information Commissioner's Office","https:\u002F\u002Fico.org.uk\u002Ffor-organisations\u002Fuk-gdpr-guidance-and-resources\u002F","The UK's version of the GDPR, including rules on solely automated decisions.",81,{"id":425,"label":426,"issuer":137,"region":138,"url":427,"description":428,"useCases":429,"indexable":207},"dora","DORA","https:\u002F\u002Feur-lex.europa.eu\u002Feli\u002Freg\u002F2022\u002F2554\u002Foj","Digital Operational Resilience Act for financial entities: ICT risk, incident reporting and third party risk, including AI providers.",72,{"id":431,"label":432,"issuer":433,"region":138,"url":434,"description":435,"useCases":436,"indexable":207},"uk-consumer-duty","FCA Consumer Duty","Financial Conduct Authority","https:\u002F\u002Fwww.fca.org.uk\u002Ffirms\u002Fconsumer-duty","UK rules that require firms to deliver good outcomes for retail customers, including through automated channels.",51,{"id":438,"label":439,"issuer":440,"region":441,"url":442,"description":443,"useCases":444,"indexable":207},"mas-ai-risk-management","MAS AI risk management guidelines","Monetary Authority of Singapore","asia-pacific","https:\u002F\u002Fwww.mas.gov.sg\u002Fnews\u002Fmedia-releases\u002F2025\u002Fmas-guidelines-for-artificial-intelligence-risk-management","Singapore's supervisory expectations for AI risk management at financial institutions, building on the FEAT principles.",37,{"id":446,"label":447,"issuer":448,"region":441,"url":449,"description":450,"useCases":451,"indexable":207},"apra-cps-230","APRA CPS 230","Australian Prudential Regulation Authority","https:\u002F\u002Fwww.apra.gov.au\u002Foperational-risk-management","Australian operational risk standard covering critical operations and material service providers.",26,{"id":453,"label":454,"issuer":455,"region":247,"url":456,"description":457,"useCases":458,"indexable":207},"us-sr-11-7","SR 11-7 model risk management","Federal Reserve and OCC","https:\u002F\u002Fwww.federalreserve.gov\u002Fboarddocs\u002Fsrletters\u002F2011\u002Fsr1107.htm","US supervisory guidance on model risk management, applied by banks to AI and machine learning models.",23,{"id":460,"label":461,"issuer":137,"region":138,"url":462,"description":463,"useCases":464,"indexable":207},"nis2","NIS2 Directive","https:\u002F\u002Feur-lex.europa.eu\u002Feli\u002Fdir\u002F2022\u002F2555\u002Foj","Directive (EU) 2022\u002F2555 on cybersecurity for essential and important entities, including telecom networks, energy and public administration.",22,{"id":466,"label":467,"issuer":468,"region":144,"url":469,"description":470,"useCases":464,"indexable":207},"pci-dss","PCI DSS","PCI Security Standards Council","https:\u002F\u002Fwww.pcisecuritystandards.org\u002F","Security standard for any system that stores, processes or transmits cardholder data.",{"id":472,"label":473,"issuer":474,"region":138,"url":475,"description":476,"useCases":477,"indexable":207},"uk-atrs","UK Algorithmic Transparency Recording Standard","UK Government","https:\u002F\u002Fwww.gov.uk\u002Fgovernment\u002Fcollections\u002Falgorithmic-transparency-recording-standard-hub","Mandatory transparency records for algorithmic tools used by UK central government.",18,{"id":479,"label":480,"issuer":481,"region":247,"url":482,"description":483,"useCases":484,"indexable":207},"hipaa","HIPAA","US Department of Health and Human Services","https:\u002F\u002Fwww.hhs.gov\u002Fhipaa\u002Findex.html","US rules for the privacy and security of protected health information.",17,{"id":486,"label":487,"issuer":488,"region":144,"url":489,"description":490,"useCases":491,"indexable":207},"fatf-recommendations","FATF Recommendations","Financial Action Task Force","https:\u002F\u002Fwww.fatf-gafi.org\u002Fen\u002Fpublications\u002FFatfrecommendations\u002FFatf-recommendations.html","Global standards for anti money laundering and counter terrorist financing that national rules implement.",15,{"id":493,"label":494,"issuer":137,"region":138,"url":495,"description":496,"useCases":497,"indexable":207},"eu-amlr","EU Anti Money Laundering Regulation","https:\u002F\u002Feur-lex.europa.eu\u002Feli\u002Freg\u002F2024\u002F1624\u002Foj","Regulation (EU) 2024\u002F1624: the single EU rulebook for customer due diligence, beneficial ownership and suspicious transaction reporting.",14,{"id":499,"label":500,"issuer":501,"region":247,"url":502,"description":503,"useCases":497,"indexable":207},"us-tcpa","Telephone Consumer Protection Act","Federal Communications Commission","https:\u002F\u002Fwww.fcc.gov\u002Fconsumers\u002Fguides\u002Fstop-unwanted-robocalls-and-texts","US consent rules for automated and prerecorded calls and texts; the FCC has confirmed AI generated voices count as artificial voices.",{"id":505,"label":506,"issuer":507,"region":247,"url":508,"description":509,"useCases":510,"indexable":207},"us-bsa","Bank Secrecy Act","FinCEN","https:\u002F\u002Fwww.fincen.gov\u002Fresources\u002Fstatutes-and-regulations\u002Fbank-secrecy-act","US anti money laundering law: customer due diligence, suspicious activity reports and record keeping.",13,{"id":512,"label":513,"issuer":137,"region":138,"url":514,"description":515,"useCases":510,"indexable":207},"eu-accessibility-act","European Accessibility Act","https:\u002F\u002Feur-lex.europa.eu\u002Feli\u002Fdir\u002F2019\u002F882\u002Foj","Directive (EU) 2019\u002F882: accessibility requirements for banking services, ecommerce and other digital services, applicable since June 2025.",{"id":517,"label":518,"issuer":137,"region":138,"url":519,"description":520,"useCases":510,"indexable":207},"solvency-ii","Solvency II","https:\u002F\u002Feur-lex.europa.eu\u002Feli\u002Fdir\u002F2009\u002F138\u002Foj","Directive 2009\u002F138\u002FEC: risk based capital, governance and model requirements for insurers.",{"id":522,"label":523,"issuer":524,"region":247,"url":525,"description":526,"useCases":527,"indexable":207},"us-ecoa-reg-b","ECOA and Regulation B","Consumer Financial Protection Bureau","https:\u002F\u002Fwww.consumerfinance.gov\u002Frules-policy\u002Fregulations\u002F1002\u002F9\u002F","US fair lending rules, including specific reasons in adverse action notices, which also apply when credit decisions use AI models.",12,{"id":529,"label":530,"issuer":531,"region":144,"url":532,"description":533,"useCases":527,"indexable":207},"telecom-consumer-rules","Telecom consumer protection rules","National telecom regulators","https:\u002F\u002Fwww.berec.europa.eu\u002F","National rules on telecom contracts, switching, billing disputes and marketing consent.",{"id":535,"label":536,"issuer":537,"region":138,"url":538,"description":539,"useCases":372,"indexable":207},"eba-loan-origination","EBA Guidelines on loan origination and monitoring","European Banking Authority","https:\u002F\u002Fwww.eba.europa.eu\u002Fregulation-and-policy\u002Fcredit-risk\u002Fguidelines-on-loan-origination-and-monitoring","Expectations for credit decisioning, including the use of automated models.",{"id":541,"label":542,"issuer":137,"region":138,"url":543,"description":544,"useCases":372,"indexable":207},"eecc","European Electronic Communications Code","https:\u002F\u002Feur-lex.europa.eu\u002Feli\u002Fdir\u002F2018\u002F1972\u002Foj","Directive (EU) 2018\u002F1972: consumer protection, contract, switching and security rules for telecom operators.",{"id":546,"label":547,"issuer":137,"region":138,"url":548,"description":549,"useCases":372,"indexable":207},"eu-psd2","PSD2","https:\u002F\u002Feur-lex.europa.eu\u002Feli\u002Fdir\u002F2015\u002F2366\u002Foj","Payment Services Directive 2: strong customer authentication, transaction risk analysis exemptions and open banking access.",{"id":551,"label":552,"issuer":440,"region":441,"url":553,"description":554,"useCases":555,"indexable":207},"mas-notice-626","MAS Notice 626","https:\u002F\u002Fwww.mas.gov.sg\u002Fregulation\u002Fnotices\u002Fnotice-626","Singapore's anti money laundering and counter terrorism financing requirements for banks.",10,{"id":557,"label":558,"issuer":137,"region":138,"url":559,"description":560,"useCases":555,"indexable":207},"mifid-ii","MiFID II","https:\u002F\u002Feur-lex.europa.eu\u002Feli\u002Fdir\u002F2014\u002F65\u002Foj","Directive 2014\u002F65\u002FEU on markets in financial instruments: suitability and appropriateness of advice, record keeping and product governance.",{"id":562,"label":563,"issuer":564,"region":247,"url":565,"description":566,"useCases":55,"indexable":207},"us-fcra","Fair Credit Reporting Act","Federal Trade Commission","https:\u002F\u002Fwww.ftc.gov\u002Flegal-library\u002Fbrowse\u002Fstatutes\u002Ffair-credit-reporting-act","US rules on consumer reports, their accuracy and permissible use, relevant to credit scoring and screening.",{"id":568,"label":569,"issuer":137,"region":138,"url":570,"description":571,"useCases":309,"indexable":207},"eu-idd","Insurance Distribution Directive","https:\u002F\u002Feur-lex.europa.eu\u002Feli\u002Fdir\u002F2016\u002F97\u002Foj","Directive (EU) 2016\u002F97: conduct rules for selling insurance, including demands and needs testing and advice.",{"id":573,"label":574,"issuer":575,"region":576,"url":577,"description":578,"useCases":579,"indexable":207},"cbuae-ai-guidance","CBUAE guidance on AI and ML","Central Bank of the UAE","middle-east","https:\u002F\u002Fwww.centralbank.ae\u002F","UAE central bank expectations for the enabling technologies, AI and machine learning used by licensed financial institutions.",5,{"id":581,"label":582,"issuer":137,"region":138,"url":583,"description":584,"useCases":388,"indexable":207},"eu-mortgage-credit-directive","EU Mortgage Credit Directive","https:\u002F\u002Feur-lex.europa.eu\u002Feli\u002Fdir\u002F2014\u002F17\u002Foj","Directive 2014\u002F17\u002FEU: creditworthiness assessment, disclosure and advice rules for residential mortgage lending.",{"id":586,"label":587,"issuer":588,"region":138,"url":589,"description":590,"useCases":388,"indexable":207},"pra-ss1-23","PRA SS1\u002F23 model risk management","Prudential Regulation Authority","https:\u002F\u002Fwww.bankofengland.co.uk\u002Fprudential-regulation\u002Fpublication\u002F2023\u002Fmay\u002Fmodel-risk-management-principles-for-banks-ss","UK model risk management principles for banks, covering AI and machine learning models.",{"id":592,"label":593,"issuer":594,"region":138,"url":595,"description":596,"useCases":388,"indexable":207},"uk-psr-app-reimbursement","UK APP scam reimbursement rules","Payment Systems Regulator","https:\u002F\u002Fwww.psr.org.uk\u002Four-work\u002Fapp-scams\u002F","Mandatory reimbursement of authorised push payment scam victims by UK payment firms, which shifts scam losses onto banks.",{"id":598,"label":599,"issuer":600,"region":441,"url":601,"description":602,"useCases":357,"indexable":207},"au-scams-prevention-framework","Australian Scams Prevention Framework","Australian Treasury","https:\u002F\u002Ftreasury.gov.au\u002Fconsultation\u002Fc2024-573813","Economy wide obligations for banks, telcos and digital platforms to prevent, detect, disrupt and respond to scams.",{"id":604,"label":605,"issuer":137,"region":138,"url":606,"description":607,"useCases":357,"indexable":207},"eu-mar","EU Market Abuse Regulation","https:\u002F\u002Feur-lex.europa.eu\u002Feli\u002Freg\u002F2014\u002F596\u002Foj","Regulation (EU) 596\u002F2014: insider dealing and market manipulation, including the duty to detect and report suspicious orders and transactions.",{"id":609,"label":610,"issuer":611,"region":247,"url":612,"description":613,"useCases":357,"indexable":207},"nyc-local-law-144","NYC Local Law 144","New York City","https:\u002F\u002Fwww.nyc.gov\u002Fsite\u002Fdca\u002Fabout\u002Fautomated-employment-decision-tools.page","Bias audits and notices for automated employment decision tools used in hiring and promotion in New York City.",1791904356392]